Rate-aided multisignal time delay detection and tracking

Time delay detection and tracking problems have been investigated in previous papers. The approach used is applicable to many problems. In those papers, a first-order Markov process was assumed for the signal parameter (time delay) dynamic model and a constant signal parameter value was assumed within a “block”, or processing unit of time. A performance degradation is incurred when the signal parameter value is “nearly constant-rate”. Also, “crossing” signal parameter values from different signals cannot be tracked. The detector-trackers will “switch” signals. To combat these difficulties, the signal parameter dynamic model is assumed to be a second-order Markov process, and signal parameter rate of change information is computed within a block. A rate-aided multisignal detection and tracking system is developed with these assumptions     

Optimum time delay detection and tracking

An optimum solution to the time delay tracking problems has been previously achieved by recursively computing the time-delay posterior probability density function (PDF), or time-delay PDF conditioned on knowing all observed data, by numerical means. Any optimum estimate is determined from the posterior PDF. The same approach is extended to an optimum solution for the time delay detection problem with a randomly appearing and disappearing signal. The detector-tracker is suitable for a stand-alone detection and tracking system     

Hypotheses Testing in a Distributed Environment

The problem of optimum detection with n decentralized sensors selecting among m possible signals is considered from the decision theory point of view. The loss function is defined in terms of the decisions made by each observer and the transmitted signal. Then the average of this loss function is minimized. This leads to sets of coupled inequalities in terms of the likelihood ratio of each observer and the decisions made at the other sensors. This determines the structure of the optimum decentralized detection for an arbitrary number of sensors and an arbitrary number of possible signals. These results are valuable in numerous situations that may arise in large-scale and distributed systems.     

A PDF multitarget tracker

A probability density function (pdf) based approach to the multitarget tracking problem is presented. The input data are obtained by measurements over time from a front-end detector. The desired output is the number of targets present and the parameters of each target. The same approach has previously been used for time delay detection and tracking problems and is adapted to this problem This approach is an alternative to the traditional approach of “association” and “tracking” on the measurements     

宽带信号角跟踪和四通道单脉冲方案

分析了宽带信号角跟踪的特殊问题及其实现方案。基于互相关函数的角误差检测方法,推导出了在非相关噪声及相关噪声背景下差路信号的输出信噪比及其角度随机误差的数学表达式,进而给出了带宽增益和最佳带宽的概念,以及提高输出信噪比的方法。为了在低载噪比（C/N）时获得角捕获所需要的和路信号以及差路的归一化信号,提出了四通道单脉冲方案。最后归纳出了低C/N时宽带信号角捕获和角跟踪的几种方法并提出了建议。     

A Recursive Method for Signal Resolution

A recursive method is given for resolving signals overlapping in time. Assume that the signal waveform is known and several signals are received. The signals (of unknown number) may overlap with one another and the amount of time delay of each individual signal is unknown. The signals are corrupted with additive white Gaussian noise. The problem is to estimate the number, the amplitudes, and the time delays of the overlapping signals. Assume that at a certain instant tk-1 estimates have been made on the number of signals arriving in the time interval (O, tk-1) and the amplitudes and time delays of these signals. Using these estimates, we test at tk the hypothesis H1 that a new signal arrives at tk against the null hypothesis Ho that no new signal arrives. The decision gives the number of signals arriving in the time interval (0, tk); the parameters are then re-estimated. The overlapping signals are detected and resolved, and the estimates are improved at each stage. The system is analyzed in detail, and computer-simulated results are presented.     

Bayesian Quickest Signal Detection in a Discrete-Time Observation

This paper deals with the problem of quickest detection of a signal in discrete-time observations where the noise is not necessarily additive. By introducing a new cost function, penalizing the decision delay, in addition to penalizing wrong decisions as in the classical case, a global risk function is derived for use in a Bayesian framework. The minimization of the average risk leads to the optimum Bayesian decision regions, giving the structure of the optimum receiver. Some simplifications for elementary costs and some applications are investigated. The optimum receiver is shown to be a parallel bank of classical optimum filters, each one matched to a particular delay of the signal to be detected. Our approach is shown to apply to the detection of certain changes in a stochastic process.     

存在外部干扰的网络控制系统故障检测和优化

针对存在时延和丢包的网络控制系统,研究了系统的故障检测滤波器设计和优化设计问题.通过泰勒展开将未知时延处理成外界干扰,采用伯努利随机过程来描述丢包现象.设计观测器产生残差信号,将故障检测问题转化为H∞滤波问题.通过Lyapunov函数方法分析了系统的稳定性.以线性矩阵不等式的形式给出了滤波器存在的充分条件和求解方法.为进一步提高系统对故障信号的灵敏度,采用了一种优化设计方法对故障检测系统进行了优化.最后通过仿真验证了算法的有效性.     

Microprocessor Matched Filtering of Emergency Chirp Signals

A microcomputer matched filter solution is suggested for identifying emergency locator transmitter (ELT) signals from aircraft in distress. A sliding fast Fourier transform (FFT) with adjustable delay covers all permissible ELT sweep rates. The sweep rate for optimum response is retained for signal classification purposes. An additional nonsliding FFT is used to test for the possible presence of monotone modulation in the frequency range of the ELT, and an additional uncorrelated test helps establish a background reference level for positive ELT identiflcation.     

Periodic acoustic source tracking using propagation delayed measurements

There exist a large class of acoustic sources which have an underlying periodic phenomenon. Unlike the well-studied Bearings-Only Tracking(BOT) of an aperiodic acoustic source,this paper considers the problem of tracking a periodic acoustic source. For periodic acoustic tracking, the signal emission time is known. However, the true measurement reception time is unknown because it is corrupted by noise due to propagation delay. We augment the sensor’s signal reception time onto bearing measuremen...     

基于数字包络检波的RNSS通道时延标定方法

提出一种采用数字处理的时延测试方法,用于对导航卫星导航信号发射通道分数码片时延的精确测量。该方法是通过高速A/D（模/数）转换器,对导航卫星下行的BPSK（二进制相移键控）信号和卫星导航秒脉冲进行双通道采样,读取采样数据并进行数据处理。根据秒脉冲信号触发门限上升沿确定时延测量起点,对BPSK采样数据进行平方律检波,获取码片换相点,计算换相点和秒脉冲之间的分数码片时延,并进行滤波器时延校准,从而得到导航卫星发射链路的分数码片时延,该方法不需要进行伪随机信号的捕获和跟踪,测量精度主要取决于采样器采样率。通过在测试中使用一根校准电缆对该方法进行验证,验证结果表明,采用本文提出测试方法的测量误差优于0.3ns。     

Multipath Angle Error Reduction Using Multiple-Target Methods

The usual methods of reducing multipath angle errors in monopulse tracking radar achieve only limited success because they do not attack the root of the problem. A more correct approach is to accept the multipath signal as a second target and utilize a two-target signal processor which angle tracks both wavefronts. The processor will decouple the return signals so that relatively interference-free data on both waves are obtained. In this paper a signal processor for separating signal from (N - 1) multipath components is developed. The processor is then specialized to the case of only one multipath signal and evaluated by a computer simulation. Data show that large improvements are possible as compared to the usual monopulse tracking system. In particular, the usual large bias errors at low elevation angles are eliminated. Tracking precision compares favorably with the theoretically best possible for two-target tracking systems.     

高斯非平稳机动目标波达角模型及跟踪

在实际的跟踪情况中,由于环境条件、目标反射截面等因素的变化,回波信号的功率会随时间变化,即不满足通常阵列信号处理中对高斯信号作平稳性的假设。针对复杂运动条件下高斯非平稳目标的跟踪问题,提出了一种新的机动目标波达角(DOA)模型。该模型全面地刻画了高斯非平稳机动目标的动态,并将目标的DOA和信号功率作为状态变量进行了联合考虑,同时运用虚拟阵列的表示方法构建了相应的观测方程。对于建立的新模型,最后采用无迹卡尔曼滤波(UKF)的框架完成了整个跟踪算法。分析和仿真结果表明,当高斯非平稳机动目标之间存在长时间相互接近的情况时,新方法仍然可以获得较好的跟踪性能。     

Application of successive interference cancellation to the GPS pseudolite near-far problem

Ground-based transmitters called pseudolites have been proposed to augment the basic Global Positioning System (GPS) in environments where satellite visibility is limited. One difficulty in their use is the so-called near-far problem, where in close proximity to the ground transmitter, the pseudolite signal can be orders of magnitude stronger than the satellite signals. This large range of signal levels prevents a conventional receiver from simultaneously detecting both types of signals. This paper describes the application of a signal processing technique, known as successive interference cancellation (SIC), to the acquisition and tracking of weak satellite signals in the presence of a nearby pseudolite and possible multipath reflections of this pseudolite signal. The SIC architecture is implemented on simulated and experimental near-far data sets. The results are compared with a conventional detector and improvements in acquisition and tracking performance are illustrated.     

An Optimum First-Order Time Delay Tracker

The key to the general estimation problem is the computation ofthe posterior probability density function (PDF) of the desiredparameter, or PDF conditioned on knowing all availableobservations. Any optimum estimate can be computed from this PDF. The theory and implementation of a numerical solution ispresented for the computation of the posterior PDF in real time fortime delay tracking with a first-order Markov assumption. Benefitsinclude a lack of threshold effects usually associated with nonlineartrackers as well as theoretically optimum performance.     

Optimum Realizable Continuous Range Estimation

The ability to detect the presence or absence of a target is no longer the fundamental design criterion when the vehicle to be tracked is cooperative. In spacecraft tracking or navigation systems, for example, emphasis is placed on post-acquisition performance. Therefore, classical radar theory and design techniques are not specifically applicable. On the other hand, there are optimization techniques for extracting the tracking data from noise that are more to the point. In particular, optimum demodulation theory is directed specifically to the problem of continuously extracting data from a nonlinear modulation process. In this paper, the tracking properties of a multitone PM ranging signal are reviewed and are shown to be nearly optimum for cooperative vehicles. An optimum, but nonrealizable, maximum a posteriori (MAP) continuous estimator of range is derived for this signal. The linearized model of this receiver is the optimum nonrealizable Wiener filter for the data. Interpretation of this optimum nonrealizable estimator leads to a receiver design that is both practical and intuitively satisfying. With the aid of post-detection processing in the Wiener-Hopf sense, almost optimum performance is obtained from the resulting receiver, above threshold.     

An Adaptive Array Signal Processing Algorithm for Communications

An algorithm is described for initial synchronization in a communication system with a digital adaptive array. This algorithm can also be used for message extraction. A set of consecutive complex video samples of the array output is processed to obtain optimum adaptive array weights, based on a least mean square (LMS) error criterion. This computation is performed for each of the possible alternative signals which may be present during an observation interval. The correct synchronization time or message symbol is selected as the one which yields the minimum LMS error. Assuming orthogonality of the alternative codes, a probability distribution for the output of this processor has been derived.     

Quickest detection for sequential decentralized decision systems

Quickest detection procedures are techniques used to detect sudden or abrupt changes (also called disorders) in the statistics of a random process. The goal is to determine as soon as possible that the change occurred, while at the same time minimizing the chance of falsely signaling the occurrence of a disorder before the change. In this work the distributed quickest detection problem when the disorder occurs at an unknown time is considered. The distributed local detectors utilize a simple summing device and threshold comparator, with a binary decision at the output. At the fusion center, the optimal maximum likelihood (ML) procedure is analyzed and compared with the more practical Page procedure for quickest detection. It is shown that the two procedures have practically equivalent performance. For the important case of unknown disorder magnitudes, a version of the Hinkley procedure is also examined. Next, a simple method for choosing the thresholds of the local detectors based on an asymptotic performance measure is presented. The problem of selecting the local thresholds usually requires optimizing a constrained set of nonlinear equations; our method admits a separable problem, leading to straightforward calculations. A sensitivity analysis reveals that the resulting threshold settings are optimal for practical purposes. The issue of which sample size to use for the local detectors is investigated, and the tradeoff between decision delay and communication cost is evaluated. For strong signals, it is shown that the relative performance deteriorates as the sample size increases, that is, as the system cost decreases. Surprisingly, for the weak signal case, lowering the system cost (increasing the sample size) does not necessarily result in a degradation of performance     

空中交通流量优化管理

研究了空中交通流量管理中的机场流量最优化问题,提出了解决目前日益严重的拥塞问题的一种方案,将机场流量利用最优化问题分解为两个子问题,以折考虑解的最优性及求解复杂性,针对两个子问题,提出了一种折考虑解的最优性及求解复杂性的线性规划数学模型,利用该模型,可以最有效地发挥系统功能,同是保证飞机飞行过程的有效隔离,最后,还给出了具体的实例分析,证实了所建模型的实用性。     

基于阶次小波包的转子加速阶段振动故障研究

针对发动机转子在加速阶段的振动信号为非稳态、且该阶段的振动信号无法直接使用谱分析等技术处理的问题,提出了利用改进的阶次跟踪分析技术对信号进行等角度重采样,将时域非稳态信号转换为角域稳态信号,然后对信号进行小波包分析及能量特征向量提取。结果表明,利用阶次小波包方法可以很好地处理变速振动信号,效果好于直接使用小波包分析非稳态的时域信号,计算后的结果可用于进一步的数据处理。